TY - JOUR A1 - Dachwald, Bernd A1 - Ohndorf, A. T1 - 1st ACT Global Trajectory Optimisation Competition : Results found at DLR JF - Acta Astronautica. 61 (2007), H. 9 Y1 - 2007 SN - 0094-5765 N1 - Global Trajectory Optimization ; Results of the First Competition Organised by the Advanced Concept Team (ACT) of the European Space Agency (ESA) SP - 742 EP - 752 ER - TY - JOUR A1 - Kreyer, Jörg A1 - Müller, Marvin A1 - Esch, Thomas T1 - A Calculation Methodology for Predicting Exhaust Mass Flows and Exhaust Temperature Profiles for Heavy-Duty Vehicles JF - SAE International Journal of Commercial Vehicles N2 - The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition. In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon. To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed. Y1 - 2020 U6 - http://dx.doi.org/10.4271/02-13-02-0009 SN - 1946-3928 VL - 13 IS - 2 SP - 129 EP - 143 PB - SAE International CY - Warrendale, Pa. ER - TY - JOUR A1 - Dachwald, Bernd A1 - Tsinas, L. T1 - A combined neural and genetic learning algorithm / Tsinas, L. ; Dachwald, B. JF - Proceedings of the First IEEE Conference on Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence. Y1 - 1994 SN - 0-7803-1899-4 SP - 770 EP - 774 CY - Orlando, Fl ER - TY - JOUR A1 - Gerhardt, Hans Joachim A1 - Cooper, K.-R. A1 - Whitbread, R. A1 - Gary, K.-P. (u.a.) T1 - A comparison of aerodynamic drag measurements on model trucks in closed-jet and open-jet wind tunnels Y1 - 1985 N1 - Konferenz-Einzelbericht : 6th Colloquium on Industrial Aerodynamics, Road Vehicle Aerodynamics, Fachhochschule Aachen, 19.-21.6.1985 SP - 261 EP - 274 ER - TY - JOUR A1 - Harder, Jörn T1 - A crystallographic model for the study of local deformation processes in polycrystals JF - International journal of plasticity. 15 (1999), H. 6 Y1 - 1999 SN - 0749-6419 N1 - Online: http://opus.tu-bs.de/opus/volltexte/1999/10/pdf/10_1.pdf SP - 605 EP - 624 ER - TY - JOUR A1 - Schmitz, Günter A1 - Roetert, J. A1 - Pischinger, M. T1 - A Fast Intelligent VMEbus System for Combustion Analysis in Engines JF - 19th [nineteenth] International Symposium on Automotive Technology & [and] Automation : with particular reference to cell control and quality management systems for the manufacturing industries; Monte Carlo, 24. - 28. October 1988. Y1 - 1988 SN - 0947719229 SP - 381 EP - 391 PB - Automotive Automation Ltd CY - Croydon ER - TY - JOUR A1 - Weber, Tobias A1 - Arent, Jan-Christoph A1 - Münch, Lukas A1 - Duhovic, Miro A1 - Balvers, Johannes M. T1 - A fast method for the generation of boundary conditions for thermal autoclave simulation JF - Composites Part A N2 - Manufacturing process simulation enables the evaluation and improvement of autoclave mold concepts early in the design phase. To achieve a high part quality at low cycle times, the thermal behavior of the autoclave mold can be investigated by means of simulations. Most challenging for such a simulation is the generation of necessary boundary conditions. Heat-up and temperature distribution in an autoclave mold are governed by flow phenomena, tooling material and shape, position within the autoclave, and the chosen autoclave cycle. This paper identifies and summarizes the most important factors influencing mold heat-up and how they can be introduced into a thermal simulation. Thermal measurements are used to quantify the impact of the various parameters. Finally, the gained knowledge is applied to develop a semi-empirical approach for boundary condition estimation that enables a simple and fast thermal simulation of the autoclave curing process with reasonably high accuracy for tooling optimization. Y1 - 2016 U6 - http://dx.doi.org/10.1016/j.compositesa.2016.05.036 SN - 1359-835X VL - 88 SP - 216 EP - 225 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Ulmer, Jessica A1 - Braun, Carsten A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation JF - International Journal of Production Research N2 - Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines. KW - Human factors KW - assistance system KW - gamification KW - adaptive systems KW - manufacturing Y1 - 2023 U6 - http://dx.doi.org/10.1080/00207543.2023.2166140 SN - 0020-7543 (Print) SN - 1366-588X (Online) PB - Taylor & Francis ER - TY - JOUR A1 - Konstantinidis, Konstantinos A1 - Flores Martinez, Claudio A1 - Dachwald, Bernd A1 - Ohndorf, Andreas A1 - Dykta, Paul A1 - Bowitz, Pascal A1 - Rudolph, Martin A1 - Digel, Ilya A1 - Kowalski, Julia A1 - Voigt, Konstantin A1 - Förstner, Roger T1 - A lander mission to probe subglacial water on Saturn's moon enceladus for life JF - Acta astronautica Y1 - 2015 SN - 1879-2030 (E-Journal); 0094-5765 (Print) VL - Vol. 106 SP - 63 EP - 89 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Dittus, H. A1 - Turyshev, S. G. A1 - Dachwald, Bernd A1 - Blome, Hans-Joachim T1 - A Mission to Explore the Pioneer Anomaly JF - Proceedings of the 39th ESLAB Symposium "Trends in Space Science and Cosmic Vision 2020" : 19 - 21 April 2005, ESTEC, Noordwijk, the Netherlands / European Space Agency. [Comp. by: F. Favata ...] . - (ESA SP ; 588) Y1 - 2005 SN - 9290928999 N1 - ISBN der CD-ROM-Ausg.: 9290928999 ; Symposium Trends in Space Science and Cosmic Vision 2020 <2005, Noordwijk> ; ESLAB symposium <39,2005, Noordwijk> ; European Space Laboratory ; Report Number: LA-UR-05-4907 ; The Pioneer Explorer Collaboration SP - 3 EP - 10 PB - ESA Publ. Div. CY - Noordwijk ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalili, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 U6 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SN - 2169-3536 VL - 8 IS - Art. 9108222 SP - 111381 EP - 111393 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalil, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 SN - 2169-3536 U6 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SP - 1 EP - 12 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Dachwald, Bernd A1 - Ball, Andrew J. A1 - Ulamec, Stephan A1 - Price, Michael E. T1 - A small mission for in situ exploration of a primitive binary near-Earth asteroid / Ball, Andrew J. ; Ulamec, Stephan ; Dachwald, Bernd ; Price, Michael E. ; [u.a.] JF - Advances in Space Research. 43 (2009), H. 2 Y1 - 2009 SN - 0273-1177 SP - 317 EP - 324 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Böhnisch, Nils A1 - Braun, Carsten A1 - Muscarello, Vincenzo A1 - Marzocca, Pier T1 - About the wing and whirl flutter of a slender wing–propeller system JF - Journal of Aircraft N2 - Next-generation aircraft designs often incorporate multiple large propellers attached along the wingspan (distributed electric propulsion), leading to highly flexible dynamic systems that can exhibit aeroelastic instabilities. This paper introduces a validated methodology to investigate the aeroelastic instabilities of wing–propeller systems and to understand the dynamic mechanism leading to wing and whirl flutter and transition from one to the other. Factors such as nacelle positions along the wing span and chord and its propulsion system mounting stiffness are considered. Additionally, preliminary design guidelines are proposed for flutter-free wing–propeller systems applicable to novel aircraft designs. The study demonstrates how the critical speed of the wing–propeller systems is influenced by the mounting stiffness and propeller position. Weak mounting stiffnesses result in whirl flutter, while hard mounting stiffnesses lead to wing flutter. For the latter, the position of the propeller along the wing span may change the wing mode shapes and thus the flutter mechanism. Propeller positions closer to the wing tip enhance stability, but pusher configurations are more critical due to the mass distribution behind the elastic axis. Y1 - 2024 U6 - http://dx.doi.org/10.2514/1.C037542 SN - 1533-3868 SP - 1 EP - 14 PB - American Institute of Aeronautics and Astronautics ER - TY - JOUR A1 - Mertens, Josef A1 - Klevenhusen, K. D. A1 - Jakob, H. T1 - Accurate Transonic Wave Drag Prediction Using Simple Physical Models JF - AIAA-Journal. 25 (1987), H. 6 Y1 - 1987 SN - 0001-1452 SP - 799 EP - 805 ER - TY - JOUR A1 - Mertens, Josef A1 - Henke, Rolf T1 - Adaptive technologies for future civil air transport JF - Air & Space Europe. 3 (2001), H. 3-4 Y1 - 2001 SN - 1247-5793 SP - 80 EP - 82 ER - TY - JOUR A1 - Schulze, Sven A1 - Feyerl, Günter A1 - Pischinger, Stefan T1 - Advanced ECMS for hybrid electric heavy-duty trucks with predictive battery discharge and adaptive operating strategy under real driving conditions JF - Energies N2 - To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15% more efficiently by 2025 and 30% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks. KW - Energy management strategies KW - ECMS KW - CO2 emission reduction targets KW - Driving cycle recognition KW - Predictive battery discharge Y1 - 2023 U6 - http://dx.doi.org/10.3390/en16135171 SN - 1996-1073 N1 - The article belongs to the Special Issue "Energy Management Strategies of Electrified Vehicles toward the Real-World Driving". VL - 16 IS - 13 PB - MDPI CY - Basel ER - TY - JOUR A1 - Weber, Tobias A1 - Ruff-Stahl, Hans-Joachim K. T1 - Advances in Composite Manufacturing of Helicopter Parts JF - International Journal of Aviation, Aeronautics, and Aerospace Y1 - 2017 U6 - http://dx.doi.org/10.15394/ijaaa.2017.1153 SN - 2374-6793 VL - 4 IS - 1 ER - TY - JOUR A1 - Götten, Falk A1 - Havermann, Marc A1 - Braun, Carsten A1 - Marino, Matthew A1 - Bil, Cees T1 - Aerodynamic Investigations of UAV Sensor Turrets - A Combined Wind-tunnel and CFD Approach JF - SciTech 2021, AIAA SciTech Forum, online, WW, Jan 11-15, 2021 Y1 - 2021 U6 - http://dx.doi.org/10.2514/6.2021-1535 SP - 1 EP - 12 PB - AIAA CY - Reston, Va. ER - TY - JOUR A1 - Gerhardt, Hans Joachim A1 - Kramer, C. T1 - Aerodynamsiche RA-Optimierung JF - Zentralblatt fuer Industriebau. 31 (1985), H. 5 Y1 - 1985 SN - 0044-4227 SP - 358 EP - 362 ER -